3 credits
Fall 2025 Lecture Distance Learning Upper Division
This course introduces fundamental techniques in data mining, i.e., the techniques that extract useful knowledge from a large amount of data. Topics include data preprocessing, exploratory data analysis, association rule mining, clustering, classification, anomaly detection, recommendation and graph analysis. Students are expected to gain the skills to formulate data mining problems, solve the problems using data mining techniques and interpret the output.
Learning Outcomes1Describe and explain the process of data mining.
2Formulate problems in real-world applications into data mining tasks and solve the problems using data mining techniques.
3Implement software programs that conduct data mining and evaluate the output of data mining programs.
4Present data mining solutions to people in scientific and other disciplines.
Prerequisites
Restrictions
made by Purdue students.